The objective of Project 1 is to detect, map and characterize polymorphic genes that contribute to variation in risk of cardiovascular disease (CVD). The focus in this Program Project (the San Antonio Family Hearth Study, SAFHS) is on extended Mexican American families ascertained without regard to disease status. During the current grant period each family member is being genotyped for 414 short tandem repeat markers in a 10 centimorgan map. Using genome screen data from the first ten genotyped families (Pedigree Set A, with nearly 500 individuals), QTLs have been detected and mapped that influence leptin, fat mass, BMI, insulin, 2 hour glucose, LDL-3-C, HDL-C, HDL2a unesterified cholesterol, evidence for linkage, additional, more closely spaced markers are being typed for use in finer scale mapping strategies. Identification of the functional alleles for a few of the best characterized of these genes will be pursued in Project 3. In Project 1, taking advantage of the resource of families with extensive genotypic and phenotypic data that has been created in the past ten years, linkage analyses will be pursued for phenotypes that exhibit substantial heritabilities but for which significant linkages were not detected in Pedigree Set A (e.g., apolipoproteins, selected lipoproteins size classes, fasting glucose, 2-hour insulin, fibrinogen, C-reactive protein, and measures of carotid intima-media thickness). Linkage signals also will be strengthened and refined for other QTLs for which significant evidence of linkage already has been detected (e.g., QTLs for BMI on chromosome 17, HDL-C on chromosome 16, insulin/glucose ratio on chromosome 3, and HDL2a unesterfied cholesterol on chromosome 8). These analyses will incorporate additional markers, and associations will be sought with polymorphisms in positional candidate genes. Several new phenotypes related to the role of adipose tissue as an endocrine organ will be examined, and the pleiotropic effects of QTLs detected in the current and proposed grant periods, on other CVD risk factors will be characterized. The longitudinal data being accumulated for the families in the SAFHS will be exploited to examine genetic effects on age-related changes in CVD risk.